Catch up on everything announced at Firebase Summit, and learn how Firebase can help you accelerate app development and run your app with confidence. Learn More

Use a custom TensorFlow Lite build

Stay organized with collections Save and categorize content based on your preferences.

If you're an experienced ML developer and the pre-built TensorFlow Lite library doesn't meet your needs, you can use a custom TensorFlow Lite build with ML Kit. For example, you may want to add custom ops.

Prerequisites

Bundling a custom TensorFlow Lite for Android

Build the Tensorflow Lite AAR:

bazel build --cxxopt='--std=c++11' -c opt        \
  --fat_apk_cpu=x86,x86_64,arm64-v8a,armeabi-v7a   \
  //tensorflow/lite/java:tensorflow-lite

This will generate an AAR file in bazel-genfiles/tensorflow/lite/java/. Publish the custom Tensorflow Lite AAR to your local Maven repository:

mvn install:install-file -Dfile=bazel-genfiles/tensorflow/lite/java/tensorflow-lite.aar -DgroupId=org.tensorflow \
  -DartifactId=tensorflow-lite -Dversion=0.1.100 -Dpackaging=aar

Finally, in your app build.gradle, override Tensorflow Lite with your custom version:

implementation 'org.tensorflow:tensorflow-lite:0.1.100'